Remediation of NAPL below the water table by steam-induced heat conduction

Previous experimental studies have shown that NAPL will be removed when it is contacted by steam. However, in full-scale operations, steam may not contact the NAPL directly and this is the situation addressed in this study. A two-dimensional intermediate scale sand box experiment was performed where an organic contaminant was emplaced below the water table at the interface between a coarse and a fine sand layer. Steam was injected above the water table and after an initial heating period the contaminant was recovered at the outlet. The experiment was successfully modeled using the numerical code T2VOC and the dominant removal mechanism was identified to be heat conduction induced boiling of the separate phase contaminant. Subsequent numerical modeling showed that this mechanism was insensitive to the porous medium properties and that it could be evaluated by considering only one-dimensional heat conduction.     

The effect of variability in industrial emissions on ozone formation in Houston, Texas

Ambient observations have indicated that high concentrations of ozone observed in the Houston/Galveston area are associated with plumes of highly reactive hydrocarbons, mixed with NO_x, from industrial facilities. Ambient observations and industrial process data, such as mass flow rates for industrial flares, indicate that the VOCs associated with these industrial emissions can have significant temporal variability. To characterize the effect of this variability in emissions on ozone formation in Houston, data were collected on the temporal variability of industrial emissions or emission surrogates (e.g., mass flow rates to flares). The observed emissions variability was then used to construct regionwide emission inventories with variable industrial emissions, and the impacts of the variability on ozone formation were examined for two types of meteorological conditions, both of which lead to high ozone concentrations in Houston. The air quality simulations indicate that variability in industrial emissions has the potential to cause increases and decreases of 10–52 ppb (13–316%), or more, in ozone concentration. The largest of these differences are restricted to regions of 10–20 km², but the variability also has the potential to increase regionwide maxima in ozone concentrations by up to 12 ppb.     

Economics and Land-Use Change in Prioritizing Private Land Conservation

Abstract:  Incentive-based strategies such as conservation easements and short-term management agreements are popular tools for conserving biodiversity on private lands. Billions of dollars are spent by government and private conservation organizations to support land conservation. Although much of conservation biology focuses on reserve design, these methods are often ineffective at optimizing the protection of biological benefits for conservation programs. Our review of the recent literature on protected-area planning identifies some of the reasons why. We analyzed the site-selection process according to three important components: biological benefits, land costs, and likelihood of land-use change. We compared our benefit-loss-cost targeting approach with more conventional strategies that omit or inadequately address either land costs or likelihood of land-use change. Our proposed strategy aims to minimize the expected loss in biological benefit due to future land-use conversion while considering the full or partial costs of land acquisition. The implicit positive correlation between the likelihood of land-use conversion and cost of land protection means high-vulnerability sites with suitable land quality are typically more expensive than low-vulnerability sites with poor land quality. Therefore, land-use change and land costs need to be addressed jointly to improve spatial targeting strategies for land conservation. This approach can be extended effectively to land trusts and other institutions implementing conservation programs.     

Towards an ecological solution to the folivore paradox: patch depletion as an indicator of within-group scramble competition in red colobus monkeys (Piliocolobus tephrosceles)

A number of socioecological models assume that within-group food competition is either weak or absent among folivorous primates. This assumption is made because their food resources are presumed to be superabundant and evenly dispersed. However, recent evidence increasingly suggests that folivore group size is food-limited, that the primates prefer patchily distributed high-quality foods, and display some of the expected responses to within-group scramble competition. To investigate this apparent contradiction between theoretical models and recent empirical data, we examined the foraging behaviour of red colobus monkeys (Piliocolobus tephrosceles) in Kibale National Park, Uganda. We found that red colobus monkeys foraged in a manner that suggests they deplete patches of preferred foods: intake rate slowed significantly during patch occupancy while movement rate, an index of foraging effort, increased. Furthermore, patch occupancy was related to the size of the feeding group and the size of the patch. These results suggest that within-group scramble competition occurs, may limit folivore group size, and should be considered in models of folivore behavioural ecology.     

基于模糊综合评判的电网应灾能力量化评估*

为应对极端自然灾害下电网在灾前、灾后应灾能力评估的不足,提出基于模糊综合评判的电网应灾能力量化评估方法。通过分析电网系统的综合数据和关联指标,建立电网灾前承受力和灾后恢复力评估指标体系;运用层次分析法和熵权法各自求得指标主、客观权重,并依据权重占比组合成综合权重,使用模糊综合评判对电网应灾能力进行量化评估;通过案例对所提的评估进行验证。结果表明:该评估方法更加有效体现电网实际应灾能力水平,对电网应对极端自然灾害具有一定指导作用。     

Exploring bicyclist injury severity in bicycle-vehicle crashes using latent class clustering analysis and partial proportional odds models

Introduction: Bicyclists are more vulnerable compared to other road users. Therefore, it is critical to investigate the contributing factors to bicyclist injury severity to help provide better biking environment and improve biking safety. According to the data provided by National Highway Traffic Safety Administration (NHTSA), a total of 8,028 bicyclists were killed in bicycle-vehicle crashes from 2007 to 2017. The number of fatal bicyclists had increased rapidly by approximately 11.70% during the past 10 years (NHTSA, 2019). Methods: This paper conducts a latent class clustering analysis based on the police reported bicycle-vehicle crash data collected from 2007 to 2014 in North Carolina to identify the heterogeneity inherent in the crash data. First, the most appropriate number of clusters is determined in which each cluster has been characterized by the distribution of the featured variables. Then, partial proportional odds models are developed for each cluster to further analyze the impacts on bicyclist injury severity for specific crash patterns. Results: Marginal effects are calculated and used to evaluate and interpret the effect of each significant explanatory variable. The model results reveal that variables could have different influence on the bicyclist injury severity between clusters, and that some variables only have significant impacts on particular clusters. Conclusions: The results clearly indicate that it is essential to conduct latent class clustering analysis to investigate the impact of explanatory variables on bicyclist injury severity considering unobserved or latent features. In addition, the latent class clustering is found to be able to provide more accurate and insightful information on the bicyclist injury severity analysis. Practical Applications: In order to improve biking safety, regulations need to be established to prevent drinking and lights need to be provided since alcohol and lighting condition are significant factors in severe injuries according to the modeling results.     

Modelling Replicated Weed Growth Data using Spatially-varying Growth Curves

Weed growth in agricultural fields constitutes a major deterrent to the growth of crops, often resulting in low productivity and huge losses for the farmers. Therefore, proper understanding of patterns in weed growth is vital to agricultural research. Recent advances in Geographical Information Systems (GIS) now allow geocoding of agricultural data, which enable more sophisticated spatial analysis. Our current application concerns the development of statistical models for conducting spatial analysis of growth patterns in weeds. Our data comes from an experiment conducted in Waseca, Minnesota, that recorded growth of the weed Setariaspp. We capture the spatial variation in Setaria spp. growth using spatially-varying growth curves. An added challenge is that these designs are spatially replicated, with each plot being a lattice of sub-plots. Therefore, spatial variation may exist at different resolutions – a macro level variation between the plots and micro level variation between the sub-plots nested within each plot. We develop a Bayesian hierarchical framework for this setting. Flexible classes of models result which are fitted using simulation-based methods.     

基于大面积网格法的商场疏散时间预测

为了准确预测商场人员疏散时间,文中结合群集流动规律及离散法建立新的大面积网格算法,将时间离散为微小单元Δt,空间离散为大面积网格,利用人员流动速度—密度公式,计算每一Δt时间内网格中人员流动速度,迭代累计各单元时间得到疏散时间。以某商场人员疏散演练为例进行分析,结果表明,大面积网格算法预测的人员疏散时间与实际疏散演习时间基本吻合,其相对误差为3.4%,预测精确度较高。     

北京地区对流层低层臭氧及硫酸盐气溶胶的时空分布

基于OMI/Aura卫星资料,分析了北京地区2007~2016年近10a对流层O₃浓度（0~3km）、硫酸盐气溶胶光学厚度（0~2km）、SO₂（边界层以内）柱浓度时空演变特征.结果表明,近10a来北京地区O₃浓度总体呈现上升趋势,最低值在2007年,浓度为33.65 μg/m³;硫酸盐气溶胶污染总体变化呈现先下降后增长的趋势,2007年硫酸盐气溶胶污染最为严重,2011年污染最轻,对应的AOD值为0.252,但在2014年以后,硫酸盐气溶胶污染又出现增长趋势;SO₂浓度在2007~2016年总体呈现下降的变化趋势,且下降趋势明显,最高值为2007年,最低值出现在2016年,最低值比最高值降低了60.42%,但在2011年污染出现反弹.北京O₃季节变化明显,夏季高、春秋次之、冬季低;硫酸盐气溶胶污染季节特征与O₃相同;SO₂污染主要集中在冬季,采暖期污染程度高于非采暖期.     

模拟日光照射下土霉素的复合光化学转化动力学及环境归趋

环境水体中存在众多可解离的有机污染物,而不同的解离形态表现出相异的环境行为,如光化学反应活性和归趋.本文以土霉素(OTC)为例,研究了水中可解离化合物的表观光降解、光氧化等复合光化学转化动力学,并揭示了其相应的环境光化学归趋和贡献.模拟日光(λ290nm)照射下,OTC的光降解遵循准一级反应动力学,光解速率常数(k)对pH表现出明显的依赖性.这是由于随pH值升高,解离形态(i)从OTCH_2~0、OTCH~-到OTC~(2-)渐变,相应的k_i和量子产率(Φ_i)显著增大.竞争动力学实验进一步表明,·OH和~1O_2均可以氧化降解OTC,且降解速率随着pH的增大而加快.这与3种解离形态不同的去质子化程度和氧化反应活性有关.去质子化增加化合物的电子密度,利于活性氧物种的亲电攻击,从而促进光氧化反应.基于以上OTC解离形态的不同光化学转化活性,评估了环境表层水体(pH=6~9)中的复合光化学转化半减期(t_(1/2,E)).t_(1/2,E)值依赖于基质pH和季节,北纬45°晴天正午,t_(1/2,E)在0.131 h(仲夏,pH=9)到3.63 h(仲冬,pH=6)之间.多数情况下,OTC的表观光解是其最主要的光化学转化途径,~1O_2氧化次之,而·OH氧化的贡献非常小.以上结果证明了OTC不同解离形态具有不同的光化学转化动力学.因此,为了准确评价水环境中抗生素等可解离有机污染物的光化学归趋和风险,有必要综合考虑所有解离形态的复合光化学行为.